Network quality determination method, apparatus and device, and computer storage medium

Abstract

The invention discloses a network quality determination method, apparatus and device, and a computer storage medium. According to the method, the intensity of the signal in the preset time period is screened through the first threshold value, and the identification result is obtained by using the target spectrogram corresponding to the intensity of the signal in the preset time period, so that the network quality can be comprehensively determined according to multiple indexes above the change condition of the threshold value and the signal intensity in the preset time period; therefore, the accuracy of network quality determination is improved.

Description

Technical Field

[0001] The present invention relates to the field of wireless networks, and in particular to a method, apparatus, device, computer storage medium and computer program product for determining network quality. Background Art

[0002] At present, most households’ Internet traffic is carried through wireless networks, so the coverage of home wireless networks directly determines the user experience.

[0003] In the related art, a gateway probe device is usually used to collect relevant data of terminal devices, and the network quality of the home wireless network is determined by dividing the threshold based on the relevant data. However, in some scenarios, such as when the signal strength fluctuates frequently above the threshold, it is impossible to determine that the network state is abnormal, resulting in low accuracy in determining the network quality. Summary of the invention

[0004] The embodiments of the present disclosure provide a method, apparatus, device, computer storage medium, and computer program product for determining network quality, which can improve the accuracy of determining network quality.

[0005] In a first aspect, an embodiment of the present disclosure provides a method for determining network quality, the method comprising:

[0006] Obtaining the signal strength of the mobile terminal within a preset time period;

[0007] When the first value corresponding to the strength of the signal within the preset time period is greater than or equal to the first threshold, converting the strength of the signal within the preset time period from the time domain to the frequency domain to obtain a target spectrum diagram, wherein the first value is the standard deviation or variance of the strength of the signal within the preset time period;

[0008] Perform image recognition on the target spectrum graph to obtain the recognition result;

[0009] When the identification result is greater than a preset judgment threshold, determining the network quality corresponding to the mobile terminal as the first target network quality;

[0010] When the identification result is less than or equal to the preset judgment threshold, it is determined that the network quality corresponding to the mobile terminal is the second target network quality.

[0011] In an achievable implementation, after obtaining the signal strength of the mobile terminal within a preset time period, the method further includes:

[0012] When a first value corresponding to the strength of the signal within the preset time period is less than a first threshold, comparing a second value corresponding to the strength of the signal within the preset time period with a second threshold, the second value being an average value of the strength of the signal within the preset time period;

[0013] If the second value corresponding to the signal strength within the preset time period is less than the second threshold, it is determined that the network quality corresponding to the mobile terminal is the third target network quality.

[0014] In an achievable implementation, when a first value corresponding to the strength of a signal within a preset time period is greater than or equal to a first threshold, converting the strength of the signal within the preset time period from a time domain to a frequency domain to obtain a target spectrum diagram includes:

[0015] The signal strengths within the preset time period are spliced ​​in chronological order to obtain a target signal strength waveform;

[0016] Slicing the target signal strength waveform to obtain multiple target image frame data;

[0017] Performing fast Fourier transform processing on multiple target image frame data respectively to obtain multiple frame spectrum data;

[0018] Combine multiple frame spectrum data to obtain the target spectrum graph.

[0019] In an achievable implementation, the signal strengths within a preset time period are spliced ​​in chronological order to obtain a target signal strength waveform, including:

[0020] The signal strengths within the preset time period are spliced ​​in chronological order to obtain an initial target signal strength waveform;

[0021] Obtain a signal strength point in the initial target signal strength waveform whose difference with any signal strength point is greater than a preset screening threshold as a discrete point;

[0022] The discrete points in the initial target signal strength waveform are deleted to obtain the target signal strength waveform.

[0023] In one practicable implementation, the target signal strength waveform is sliced ​​to obtain a plurality of target image frame data, including:

[0024] Slicing the target signal strength waveform according to a preset repetition to obtain a plurality of initial image frame data, wherein the preset repetition is used to intercept the maximum periodic waveform;

[0025] A plurality of initial image frame data are normalized to obtain a plurality of target image frame data.

[0026] In an achievable implementation, the first target network quality includes a fourth target network quality and a fifth target network quality. When the identification result is greater than a preset judgment threshold, after determining that the network quality corresponding to the mobile terminal is the first target network quality, the method further includes:

[0027] Comparing a second value corresponding to the strength of the signal within a preset time period with a second threshold value to obtain a comparison result;

[0028] When the comparison result indicates that the second value corresponding to the signal strength within the preset time period is greater than or equal to the second threshold, determining that the network quality corresponding to the mobile terminal is the fourth target network quality;

[0029] When the comparison result indicates that the second value corresponding to the signal strength within the preset time period is less than the second threshold, it is determined that the network quality corresponding to the mobile terminal is the fifth target network quality.

[0030] In one practicable implementation, after performing image recognition on the target spectrum graph and obtaining a recognition result, the method further includes:

[0031] The target confidence information is obtained by dividing the number of mobile terminals with the same network quality type by the total number of terminals, where the total number of terminals includes the mobile terminals;

[0032] The user network quality type is determined based on the target confidence information.

[0033] In a second aspect, an embodiment of the present disclosure provides a device for determining network quality, the device comprising:

[0034] An acquisition module, used to acquire the signal strength of the mobile terminal within a preset time period;

[0035] A conversion module, configured to convert the intensity of the signal within the preset time period from the time domain to the frequency domain to obtain a target spectrum diagram when a first value corresponding to the intensity of the signal within the preset time period is greater than or equal to a first threshold, wherein the first value is a standard deviation or variance of the intensity of the signal within the preset time period;

[0036] The recognition module is used to perform image recognition on the target spectrum graph to obtain a recognition result;

[0037] A determination module, configured to determine, when the recognition result is greater than a preset judgment threshold, that the network quality corresponding to the mobile terminal is the first target network quality;

[0038] The determination module is further used to determine that the network quality corresponding to the mobile terminal is the second target network quality when the identification result is less than or equal to a preset judgment threshold.

[0039] In a third aspect, an embodiment of the present disclosure provides a device for determining network quality, the device comprising a processor and a memory storing computer program instructions; the processor reads and executes the computer program instructions to implement a method for determining network quality as described in any one of the first aspects.

[0040] In a fourth aspect, an embodiment of the present disclosure provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, a method for determining network quality as described in any one of the first aspects is implemented.

[0041] In a fifth aspect, an embodiment of the present disclosure provides a computer program product, including a computer program, which, when executed by a processor, implements a method for determining network quality as described in any one of the first aspects.

[0042] The embodiment of the present disclosure provides a method, device, equipment, computer storage medium and computer program product for determining network quality. The method obtains the strength of the signal of a mobile terminal within a preset time period. When the first value corresponding to the strength of the signal within the preset time period is greater than or equal to the first threshold, the strength of the signal within the preset time period is converted from the time domain to the frequency domain to obtain a target spectrum diagram. The target spectrum diagram is image-recognized to obtain a recognition result. When the recognition result is greater than the preset judgment threshold, the network quality corresponding to the mobile terminal is determined to be the first target network quality. When the recognition result is less than or equal to the preset judgment threshold, the network quality corresponding to the mobile terminal is determined to be the second target network quality. The present disclosure screens the strength of the signal within the preset time period by the first threshold, and can determine the network quality of the mobile terminal based on the numerical value corresponding to the strength of the signal. By performing image recognition on the target spectrum diagram corresponding to the strength of the signal within the preset time period to obtain the recognition result, the network quality of the mobile terminal can be determined based on the time domain and frequency domain information corresponding to the strength of the signal. Therefore, the present disclosure comprehensively determines the network quality of the mobile terminal by the numerical value corresponding to the strength of the signal and the time domain and frequency domain information corresponding to the strength of the signal, thereby improving the accuracy of network quality determination. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solution of the embodiment of the present invention, the following is a brief introduction to the drawings required for use in the embodiment of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0044] Figure 1 It is a flowchart of a method for determining network quality provided by an embodiment of the present disclosure;

[0045] Figure 2 is a flowchart of another method for determining network quality provided by an embodiment of the present disclosure;

[0046] Figure 3 It is a flowchart of a method for obtaining a target spectrum diagram provided by an embodiment of the present disclosure;

[0047] Figure 4is a schematic diagram of a target signal strength waveform diagram provided by an embodiment of the present disclosure;

[0048] Figure 5 It is a schematic diagram of obtaining a target spectrum diagram according to a target signal strength waveform diagram provided by an embodiment of the present disclosure;

[0049] Figure 6 It is a flowchart of a method for obtaining a target signal strength waveform diagram provided by an embodiment of the present disclosure;

[0050] Figure 7 is a flow chart of a method for acquiring target image frame data provided by an embodiment of the present disclosure;

[0051] Figure 8 is a flowchart of another method for determining network quality provided by an embodiment of the present disclosure;

[0052] Fig. 9 is a flow chart of a method for determining network quality of a mobile terminal provided by an embodiment of the present disclosure;

[0053] Fig.10 is a flowchart of another method for determining network quality provided by an embodiment of the present disclosure;

[0054] Fig.11 It is a structural diagram of a device of a method for determining network quality provided by an embodiment of the present disclosure;

[0055] Fig.12 It is a structural diagram of a device for a method for determining network quality provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0056] The features and exemplary embodiments of various aspects of the present invention will be described in detail below. In order to make the purpose, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present invention, rather than to limit the present invention. For those skilled in the art, the present invention can be implemented without the need for some of these specific details. The following description of the embodiments is only to provide a better understanding of the present invention by illustrating examples of the present invention.

[0057] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "include..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0058] Before describing the technical solutions provided by the embodiments of the present disclosure, in order to facilitate understanding of the embodiments of the present disclosure, the present disclosure specifically describes the problems existing in the related technologies:

[0059] At present, there are usually two ways to test the coverage of home wireless fidelity (Wi-Fi): one is that when a home user installs new broadband, the installation and maintenance personnel conduct a wireless test in the user's home; the other is to actively detect the signal strength of the terminal through a gateway probe device, and judge the coverage of the home Wi-Fi based on a threshold model.

[0060] However, the method of having installation and maintenance personnel conduct wireless tests at user homes has the following disadvantages: 1. The number of tests is small, resulting in a certain degree of randomness and error in the test results. 2. After installing the broadband, home users may change the networking mode on their own, resulting in the test results obtained by the installation and maintenance personnel during the wireless test not being able to continuously reflect the current Wi-Fi coverage of the user's home. In one example, the process of a home user changing the networking mode is as follows: the current Wi-Fi router is placed in the living room, and the user feels that the terminal signal strength is weak in the bedroom, so the Wi-Fi router is relocated to the bedroom.

[0061] The method of actively detecting the signal strength of the terminal through the gateway probe device and judging the coverage of the home WiFi according to the threshold model also has disadvantages: if the strength of the terminal signal is detected to be above the preset threshold, according to the definition of the threshold model, the coverage of the home WiFi is normal. However, if the strength of the terminal signal is above the preset threshold and the strength of the terminal signal fluctuates frequently, it can be considered that there is still a problem with the coverage of the home WiFi, and it cannot be detected by the threshold model judgment method.

[0062] The embodiments of the present disclosure provide a method, apparatus, device, computer storage medium and computer program product for determining network quality, which can solve the above-mentioned technical problems existing in the related technologies.

[0063] The embodiment of the present disclosure obtains the signal strength of the mobile terminal within a preset time period. When the first value corresponding to the signal strength within the preset time period is greater than or equal to the first threshold, the signal strength within the preset time period is converted from the time domain to the frequency domain to obtain a target spectrum diagram. The target spectrum diagram is subjected to image recognition to obtain a recognition result. When the recognition result is greater than the preset judgment threshold, the network quality corresponding to the mobile terminal is determined to be the first target network quality. When the recognition result is less than or equal to the preset judgment threshold, the network quality corresponding to the mobile terminal is determined to be the second target network quality. The present disclosure filters the signal strength within the preset time period by the first threshold, and can determine the network quality of the mobile terminal based on the numerical value corresponding to the signal strength. By performing image recognition on the target spectrum diagram corresponding to the signal strength within the preset time period to obtain the recognition result, the network quality of the mobile terminal can be determined based on the time domain and frequency domain information corresponding to the signal strength. Therefore, the present disclosure comprehensively determines the network quality of the mobile terminal by the numerical value corresponding to the signal strength and the time domain and frequency domain information corresponding to the signal strength, thereby improving the accuracy of network quality determination.

[0064] The following is an introduction to the method for determining network quality provided by an embodiment of the present disclosure.

[0065] Figure 1 FIG. 1 is a flow chart showing a method for determining network quality provided by an embodiment of the present disclosure. Figure 1 The execution subject of the method is a backend server, and the method may include the following steps S110-S150.

[0066] S110: Acquire the signal strength of the mobile terminal within a preset time period.

[0067] The mobile terminal is a movable device, such as a mobile phone, a tablet, an intelligent sweeping robot, etc. In this embodiment, the backend server obtains the signal strength of the mobile terminal within a preset time period.

[0068] In one example, the mobile terminal is connected to a gateway and a router, and the gateway or a networking probe collects the signal strength of the mobile terminal within a preset time period and sends it to a backend server, that is, the backend server obtains the signal strength of the mobile terminal within a preset time period.

[0069] S120: When a first value corresponding to the strength of the signal within the preset time period is greater than or equal to a first threshold, convert the strength of the signal within the preset time period from the time domain to the frequency domain to obtain a target frequency spectrum.

[0070] After obtaining the signal strength of the mobile terminal within the preset time period, a first value corresponding to the signal strength within the preset time period is calculated. If the value of the first value is greater than or equal to the first threshold, the signal strength within the preset time period is converted from the time domain to the frequency domain to obtain a target frequency spectrum corresponding to the signal strength within the preset time period.

[0071] The first value is the standard deviation or variance of the signal strength within a preset time period. The first threshold represents the signal strength threshold.

[0072] The disclosed embodiment obtains a target spectrum diagram by converting the intensity of a signal within a preset time period from the time domain to the frequency domain, and is able to determine the energy distribution of the signal intensity at different frequencies, thereby facilitating subsequent identification of the characteristics of the signal intensity.

[0073] S130: Perform image recognition on the target spectrum graph to obtain a recognition result.

[0074] After the target spectrum graph is obtained, image recognition is performed on the spectrum in the target spectrum graph to obtain a recognition result.

[0075] In one example, an image recognition model such as a convolutional neural network may be used to perform image recognition on the target spectrogram.

[0076] The disclosed embodiment can identify the spectrum features by performing image recognition on the target spectrum graph, thereby determining the network quality corresponding to the mobile terminal according to the spectrum features.

[0077] S140: When the identification result is greater than a preset judgment threshold, determine that the network quality corresponding to the mobile terminal is the first target network quality.

[0078] After the recognition result is obtained, the recognition result is compared with a preset threshold value. If the recognition result is greater than the preset threshold value, the network quality corresponding to the mobile terminal is determined to be the first target network quality.

[0079] The preset threshold represents a probability threshold.

[0080] In one example, the first target network quality characterization signal power stability is relatively high.

[0081] In another example, by performing image recognition on the target spectrum graph, a recognition result is obtained. If the recognition result indicates that the probability of high signal power stability is 76% and is greater than a preset threshold of 50%, it is determined that the network quality corresponding to the mobile terminal is high signal power stability.

[0082] S150: When the identification result is less than or equal to a preset judgment threshold, determine that the network quality corresponding to the mobile terminal is the second target network quality.

[0083] If the identification result is less than or equal to the preset threshold, the network quality corresponding to the mobile terminal is determined to be the second target network quality.

[0084] In an example, the second target network quality characterization signal power stability is poor.

[0085] The present disclosure screens the strength of the signal within a preset time period by a first threshold, and can determine the network quality of the mobile terminal based on the numerical value corresponding to the strength of the signal. By performing image recognition on the target spectrum graph corresponding to the strength of the signal within the preset time period to obtain the recognition result, the network quality of the mobile terminal can be determined based on the time domain and frequency domain information corresponding to the strength of the signal. Therefore, the present disclosure comprehensively determines the network quality of the mobile terminal by the numerical value corresponding to the strength of the signal and the time domain and frequency domain information corresponding to the strength of the signal, thereby improving the accuracy of network quality determination. In one embodiment, after obtaining the strength of the signal of the mobile terminal within the preset time period, the number of strengths of the signals obtained within the preset time period is calculated. If the number of strengths of the signals obtained within the preset time period is less than the preset number threshold, that is, the number of signal strengths collected does not meet the standard, the network quality of the mobile terminal is not analyzed. For example: If a user carries a mobile terminal on a business trip for a month, and the gateway probe does not collect a sufficient number of signal strengths, the network quality of the mobile terminal is not analyzed.

[0086] In one embodiment, Figure 2 As shown, after acquiring the signal strength of the mobile terminal within a preset time period, the method for determining network quality further includes step S160 and step S170.

[0087] S160: When the first value corresponding to the strength of the signal within the preset time period is less than the first threshold, compare the second value corresponding to the strength of the signal within the preset time period with the second threshold.

[0088] After obtaining the signal strength of the mobile terminal in a preset time period, a first value corresponding to the signal strength in the preset time period is calculated. If the first value is less than a first threshold, a second value corresponding to the signal strength in the preset time period is calculated, and the second value is compared with a second threshold.

[0089] The second value is an average value of the signal strength within a preset time period. The second threshold value ensures the threshold value of the signal strength.

[0090] S170: If the second value corresponding to the signal strength within the preset time period is less than the second threshold, determine that the network quality corresponding to the mobile terminal is the third target network quality.

[0091] If it is detected that the second value corresponding to the signal strength within the preset time period is less than the second threshold, it is determined that the network quality corresponding to the mobile terminal is overall weak coverage.

[0092] The disclosed embodiment can improve the accuracy of determining the network quality corresponding to the mobile terminal by performing multiple comparisons on multiple values ​​corresponding to the signal strength within a preset time period.

[0093] In one example, if Figure 3 As shown, when the first value corresponding to the signal strength in the preset time period is greater than or equal to the first threshold, the signal strength in the preset time period is converted from the time domain to the frequency domain to obtain a target spectrum diagram, which may include steps S121-S124.

[0094] S121: splicing the signal strengths within a preset time period in chronological order to obtain a target signal strength waveform.

[0095] The strengths of the signals acquired within the preset time period are sorted and spliced ​​in chronological order to obtain a target signal strength waveform.

[0096] In one example, if Figure 4 As shown in FIG. 1 , the gateway probe can obtain the signal strength of user family A from 6:00 p.m. to 12:00 p.m. every day from month N to month N+3. According to the order of months, the signal strength of user family A from month N to month N+3 is spliced ​​to obtain the target signal strength waveform.

[0097] S122: Slice the target signal strength waveform to obtain a plurality of target image frame data.

[0098] After the target signal strength waveform is acquired, the target signal strength waveform is sliced ​​according to a preset slicing method to obtain a plurality of target image frame data.

[0099] The preset slicing method may be slicing according to a preset slicing frequency or random slicing.

[0100] The disclosed embodiment can improve the time resolution and frequency resolution, reduce spectrum leakage, and improve the accuracy of the subsequently obtained spectrum graph by slicing the target signal strength waveform graph.

[0101] S123: Perform fast Fourier transform processing on the multiple target image frame data respectively to obtain multiple frame spectrum data.

[0102] After slicing to obtain a plurality of target image frame data, fast Fourier transform processing is performed on the obtained plurality of target image frame data respectively to obtain frame spectrum data corresponding to the plurality of target image frame data.

[0103] S124: Combine multiple frame spectrum data to obtain a target spectrum graph.

[0104] After obtaining a plurality of frame spectrum data, the plurality of frame spectrum data are combined to obtain a target spectrum graph.

[0105] The disclosed embodiment obtains a target signal strength waveform by splicing the signal strengths within a preset time period, and slices, fast Fourier transforms, and combines the target signal strength waveform to obtain a more accurate spectrum graph, thereby improving the accuracy of subsequent image recognition on the spectrum graph.

[0106] In one example, the steps of obtaining a target spectrum diagram according to a target signal strength waveform diagram are as follows: Figure 5 As shown in the figure: the target signal strength waveform is sliced ​​to obtain multiple target image frames. Then each target image frame is processed by fast Fourier transform in turn to obtain the corresponding frame spectrum. Finally, the obtained multiple frame spectrum data are combined in order to obtain a spectrum diagram.

[0107] In one embodiment, Figure 6 As shown, the signal strengths within a preset time period are spliced ​​in chronological order to obtain a target signal strength waveform diagram, which may include steps S1211-S1213.

[0108] S1211: splicing the signal strengths within a preset time period in chronological order to obtain an initial target signal strength waveform.

[0109] The strengths of the signals acquired within the preset time period are sorted and spliced ​​in chronological order to obtain an initial target signal strength waveform.

[0110] S1212: Acquire a signal strength point in the initial target signal strength waveform whose difference with any signal strength point is greater than a preset screening threshold as a discrete point.

[0111] After the initial target signal strength waveform is obtained, a signal strength point whose difference with any signal strength point in the initial target signal strength waveform is greater than a preset screening threshold value can be detected by a preset detection method and used as a discrete point.

[0112] In one example, the preset detection method may include a density-based spatial clustering algorithm (Density-Based Spatial Clustering of Applications with Noise, DBSCAN).

[0113] In an example, there are 20 signal strength points in the target signal strength waveform. The signal strengths of these 20 signal strength points are in the following order: -75, -74, -73, -74, -75, -76, -75, -74, -73, -75, -85, -90, -92, -75, -74, -73, -74, -75, -76, -75. Set the parameter neighborhood radius (eps) of DBSCAN to 5 and the minimum number of points in the area radius (min_samples) to 5. For the signal strength points numbered from 1 to 10, the signal strength of each point is between -73 and -76, and the signal strength difference between these points is less than 5, so these points are all core points. For the signal strength point numbered 11, its signal strength is -85, and the signal strength difference with the previous and next points is greater than 5, so it is not a core point. For the signal strength points numbered 12 and 13, their signal strengths are -90 and -92 respectively, and the difference between their signal strengths and those of the points before and after is also greater than 5, so they are not core points either. For the signal strength points numbered 14 to 20, their signal strengths are between -73 and -76, and the difference between their signal strengths is less than 5, so these points are core points. In summary, the signal strength points numbered 11, 12, and 13 are discrete points.

[0114] S1213: Delete the discrete points in the initial target signal strength waveform to obtain the target signal strength waveform.

[0115] After the discrete points in the initial target signal strength waveform are detected, the discrete points in the initial target signal strength waveform are deleted to obtain the target signal strength waveform.

[0116] The disclosed embodiment obtains an initial target signal strength waveform and deletes discrete points in the initial target signal strength waveform, thereby removing rough edges in the initial target signal strength waveform and improving the quality of the target signal strength waveform, thereby improving the accuracy of subsequent image recognition.

[0117] In one embodiment, Figure 7 As shown, slicing the target signal strength waveform to obtain multiple target image frame data may include step S1221 and step S1222.

[0118] S1221: Slice the target signal strength waveform according to a preset repetition rate to obtain a plurality of initial image frame data.

[0119] In one embodiment, after the target signal strength waveform is acquired, the target signal strength waveform is sliced ​​based on a rolling time window with a preset repetition degree to obtain a plurality of initial image frame data.

[0120] The preset repetition rate is used to capture the maximum periodic waveform.

[0121] In one example, the relationship between the target signal strength waveform and the repeatability is expressed as formula (1).

[0122] S = a*n - a*k(n-1) (1)

[0123] Wherein, S represents the total length of the target signal intensity waveform, a represents the length of the slice image frame, n represents the number of slices, and k represents the repetition degree.

[0124] S1222: Perform normalization processing on the multiple initial image frame data to obtain multiple target image frame data.

[0125] After obtaining a plurality of initial image frame data, the plurality of initial image frame data are normalized to obtain a plurality of target image frame data.

[0126] In one example, after normalizing a plurality of initial image frame data, the waveform time domain is compressed to 1 second.

[0127] The disclosed embodiment can improve the efficiency of processing the initial image frame data by slicing and normalizing the target signal strength waveform.

[0128] In one embodiment, the first target network quality includes the fourth target network quality and the fifth target network quality. When the recognition result is greater than a preset judgment threshold, after determining that the network quality corresponding to the mobile terminal is the first target network quality, Figure 8 As shown, the method for determining network quality also includes steps S210-S230.

[0129] S210: Compare a second value corresponding to the signal strength within a preset time period with a second threshold to obtain a comparison result.

[0130] The second value corresponding to the signal strength within the preset time period is compared with the second threshold to obtain a comparison result.

[0131] S220: When the comparison result indicates that the second value corresponding to the signal strength within the preset time period is greater than or equal to the second threshold, determine that the network quality corresponding to the mobile terminal is the fourth target network quality.

[0132] If the comparison result indicates that the second value corresponding to the signal strength within the preset time period is greater than or equal to the second threshold, it is determined that the network quality corresponding to the mobile terminal is the fourth target network quality.

[0133] In an example, the fourth target network quality represents uneven signal coverage.

[0134] S230: When the comparison result indicates that the second value corresponding to the signal strength within the preset time period is less than the second threshold, determine that the network quality corresponding to the mobile terminal is the fifth target network quality.

[0135] If the comparison result indicates that the second value corresponding to the signal strength within the preset time period is less than the second threshold, it is determined that the network quality corresponding to the mobile terminal is the fifth target network quality.

[0136] In an example, the fifth target network quality characterizes uneven signal coverage and weak coverage.

[0137] After determining that the network quality corresponding to the mobile terminal is the first target network quality, the embodiment of the present disclosure compares the second value corresponding to the signal strength within a preset time period with the second threshold, and further determines the network quality type corresponding to the mobile terminal through multiple comparisons, thereby improving the accuracy of network quality determination.

[0138] In one example, a flow chart of determining the network quality of a mobile terminal is as follows: Fig. 9 As shown, in which, in S901, the strength of the signal of the mobile terminal within the preset time period is obtained. In S902, when the first value corresponding to the strength of the signal within the preset time period is greater than or equal to the first threshold, the strength of the signal within the preset time period is converted from the time domain to the frequency domain to obtain a target spectrum diagram. Then, S903 is executed to perform image recognition on the target spectrum diagram to obtain a recognition result. In S904, when the recognition result is greater than the preset judgment threshold, the network quality corresponding to the mobile terminal is determined to be the first target network quality. In S905, the second value corresponding to the strength of the signal within the preset time period is compared with the second threshold to obtain a comparison result. In S906, when the comparison result indicates that the second value corresponding to the strength of the signal within the preset time period is greater than or equal to the second threshold, the network quality corresponding to the mobile terminal is determined to be the fourth target network quality. In S907, when the comparison result indicates that the second value corresponding to the strength of the signal within the preset time period is less than the second threshold, the network quality corresponding to the mobile terminal is determined to be the fifth target network quality. In S908, when the recognition result is less than or equal to the preset judgment threshold, the network quality corresponding to the mobile terminal is determined to be the second target network quality. At S909, when the first value corresponding to the strength of the signal within the preset time period is less than the first threshold, the second value corresponding to the strength of the signal within the preset time period is compared with the second threshold. At S910, if the second value corresponding to the strength of the signal within the preset time period is less than the second threshold, it is determined that the network quality corresponding to the mobile terminal is the third target network quality.

[0139] In one embodiment, the signal strength of the non-mobile terminal within a preset time period can be obtained. The non-mobile terminal is an immovable device, and the non-mobile terminal may include terminals such as smart door locks, smart speakers, and smart cameras. When the variance or standard deviation corresponding to the signal strength within the preset time period of the non-mobile terminal is greater than or equal to the first preset threshold, the network quality corresponding to the non-mobile terminal is determined to be poor signal power stability. When the variance or standard deviation corresponding to the signal strength within the preset time period of the non-mobile terminal is less than the first preset threshold, the average value corresponding to the signal strength within the preset time period of the non-mobile terminal is compared with the second preset threshold. If the average value corresponding to the signal strength within the preset time period of the non-mobile terminal is less than the second preset threshold, the network quality of the non-mobile terminal is determined to be overall weak coverage. In one embodiment, if Fig.10 As shown, after performing image recognition on the target spectrum graph and obtaining the recognition result, the method for determining network quality further includes steps S310 and S320.

[0140] S310: Divide the number of mobile terminals with the same network quality type by the total number of terminals to obtain target confidence information.

[0141] After determining the network quality of the mobile terminal, the number of mobile terminals with the same network quality type is divided by the total number of terminals to obtain target confidence information.

[0142] The total terminal includes a mobile terminal. The target confidence information is used to determine the user type.

[0143] S320: Determine the user network quality type according to the target confidence information.

[0144] After the target confidence information is calculated, the user network quality type is determined according to the target confidence information.

[0145] In one example, the number of mobile terminals with uneven signal coverage is 4, the total number of terminals is 6, and the calculated target confidence information is 66.6%. According to the target confidence information of 66.6%, which is greater than the preset confidence threshold of 50%, the user type is determined to be an uneven signal coverage user.

[0146] In the embodiment of the present disclosure, the target confidence information is obtained by dividing the number of mobile terminals with the same network quality type by the total number of terminals. The user network quality type is determined by the target confidence information, avoiding determining the user network quality type by the network quality type of some mobile terminals, thereby improving the accuracy of determining the user network quality type.

[0147] like Fig.11 As shown, the embodiment of the present disclosure further provides a device 1100 for determining network quality, and the device 1100 for determining network quality includes:

[0148] The acquisition module 1101 is used to acquire the signal strength of the mobile terminal within a preset time period;

[0149] A conversion module 1102 is used to convert the strength of the signal in the preset time period from the time domain to the frequency domain to obtain a target spectrum diagram when a first value corresponding to the strength of the signal in the preset time period is greater than or equal to a first threshold, wherein the first value is a standard deviation or variance of the strength of the signal in the preset time period;

[0150] The recognition module 1103 is used to perform image recognition on the target spectrum graph to obtain a recognition result;

[0151] A determination module 1104, configured to determine, when the identification result is greater than a preset judgment threshold, that the network quality corresponding to the mobile terminal is the first target network quality;

[0152] The determination module 1104 is further configured to determine, when the identification result is less than or equal to a preset judgment threshold, that the network quality corresponding to the mobile terminal is the second target network quality.

[0153] The present disclosure screens the strength of the signal within a preset time period through a first threshold, and can determine the network quality of the mobile terminal based on the numerical value corresponding to the strength of the signal. By performing image recognition on the target spectrum graph corresponding to the strength of the signal within the preset time period to obtain a recognition result, the network quality of the mobile terminal can be determined based on the time domain and frequency domain information corresponding to the strength of the signal. Therefore, the present disclosure comprehensively determines the network quality of the mobile terminal through the numerical value corresponding to the strength of the signal and the time domain and frequency domain information corresponding to the strength of the signal, thereby improving the accuracy of network quality determination. In some embodiments, the network quality determination device 1100 includes a comparison module, and the comparison module is used to compare the second value corresponding to the strength of the signal within the preset time period with the second threshold when the first value corresponding to the strength of the signal within the preset time period is less than the first threshold, and the second value is the average value of the strength of the signal within the preset time period;

[0154] If the second value corresponding to the signal strength within the preset time period is less than the second threshold, it is determined that the network quality corresponding to the mobile terminal is the third target network quality.

[0155] In some embodiments, the network quality determination device 1100 includes a splicing module, which is used to splice the strength of the signal within a preset time period in a time sequence to obtain a target signal strength waveform;

[0156] Slicing the target signal strength waveform to obtain multiple target image frame data;

[0157] Performing fast Fourier transform processing on multiple target image frame data respectively to obtain multiple frame spectrum data;

[0158] Combine multiple frame spectrum data to obtain the target spectrum graph.

[0159] In some embodiments, the network quality determination device 1100 includes a splicing module, which is used to splice the strength of the signal within the preset time period in time sequence to obtain an initial target signal strength waveform;

[0160] Obtain a signal strength point in the initial target signal strength waveform whose difference with any signal strength point is greater than a preset screening threshold as a discrete point;

[0161] The discrete points in the initial target signal strength waveform are deleted to obtain the target signal strength waveform.

[0162] In some embodiments, the network quality determination apparatus 1100 includes a slicing module, the slicing module is used to slice the target signal strength waveform according to a preset repetition degree to obtain a plurality of initial image frame data, the preset repetition degree is used to intercept the maximum periodic waveform;

[0163] A plurality of initial image frame data are normalized to obtain a plurality of target image frame data.

[0164] In some embodiments, the network quality determination apparatus 1100 includes a comparison module, the comparison module being used to compare a second value and a second threshold value corresponding to the strength of a signal within a preset time period to obtain a comparison result;

[0165] When the comparison result indicates that the second value corresponding to the signal strength within the preset time period is greater than or equal to the second threshold, determining that the network quality corresponding to the mobile terminal is the fourth target network quality;

[0166] When the comparison result indicates that the second value corresponding to the signal strength within the preset time period is less than the second threshold, it is determined that the network quality corresponding to the mobile terminal is the fifth target network quality.

[0167] In some embodiments, the network quality determination apparatus 1100 includes a calculation module, the calculation module is used to divide the number of mobile terminals with the same network quality type by the total number of terminals to obtain target confidence information, the total terminals including the mobile terminals;

[0168] The user network quality type is determined based on the target confidence information.

[0169] Fig.11 Each module / unit in the device shown has the function of realizing Figures 1 to 3 , Figures 6 to 10 The functions of each step executed by the application system in the present invention can achieve the corresponding technical effects. For the sake of brevity, they will not be repeated here.

[0170] Fig.12 A schematic diagram of the hardware structure of network quality determination provided by an embodiment of the present disclosure is shown.

[0171] The network quality determination apparatus may include a processor 1201 and a memory 1202 storing computer program instructions.

[0172] Specifically, the processor 1201 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0173] The memory 1202 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 1202 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. In appropriate cases, the memory 1202 may include a removable or non-removable (or fixed) medium. In appropriate cases, the memory 1202 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 1202 is a non-volatile solid-state memory.

[0174] The memory 1202 may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk storage medium device, an optical storage medium device, a flash memory device, an electrical, optical or other physical / tangible memory storage device. Thus, typically, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., a memory device) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to an aspect of the present disclosure.

[0175] The processor 1201 implements any one of the network quality determination methods in the above embodiments by reading and executing computer program instructions stored in the memory 1202 .

[0176] In one example, the network quality determination device may further include a communication interface 1203 and a bus 1204. Fig.12As shown, the processor 1201, the memory 1202, and the communication interface 1203 are connected via a bus 1204 and communicate with each other.

[0177] The communication interface 1203 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0178] Bus 1204 includes hardware, software or both, and couples the components of the online data traffic billing device to each other. For example, but not limitation, the bus may include an accelerated graphics port (Accelerated Graphics Port, AGP) or other graphics bus, an enhanced industry standard architecture (Extended Industry Standard Architecture, EISA) bus, a front side bus (Front Side Bus, FSB), a hypertransport (Hyper Transport, HT) interconnection, an industry standard architecture (Industry Standard Architecture, ISA) bus, an infinite bandwidth interconnection, a low pin count (LPC) bus, a memory bus, a micro channel architecture (MCA) bus, a peripheral component interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a serial advanced technology attachment (SATA) bus, a video electronics standard association local (VLB) bus or other suitable bus or a combination of two or more of these. Where appropriate, bus 1204 may include one or more buses. Although the embodiments of the present invention describe and illustrate specific buses, the present invention considers any suitable bus or interconnection. In addition, in conjunction with the method for determining network quality in the above-mentioned embodiment, the embodiment of the present application also provides a computer storage medium to implement. The computer storage medium stores computer program instructions; when the computer program instructions are executed by the processor, any one of the network quality determination methods in the above embodiments is implemented.

[0179] An embodiment of the present application also provides a computer program product, including a computer program, which implements any one of the network quality determination methods in the above embodiments when the computer program is executed by a processor.

[0180] It should be clear that the present invention is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present invention is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present invention.

[0181] The functional blocks shown in the above structural block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), appropriate firmware, plug-in, function card, etc. When implemented in software, the elements of the present invention are programs or code segments used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or communication link by a data signal carried in a carrier. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, read-only memory (Read-Only Memory, ROM), flash memory, erasable read-only memory (Erasable ReadOnly Memory, EROM), floppy disks, compact disc read-only memory (Compact Disc Read-Only Memory, CD-ROM), optical discs, hard disks, optical fiber media, radio frequency (Radio Frequency, RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0182] It should also be noted that the exemplary embodiments mentioned in the present invention describe some methods or systems based on a series of steps or devices. However, the present invention is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiments, or in a different order from the embodiments, or several steps can be performed simultaneously.

[0183] Aspects of the present disclosure are described above with reference to the flowchart and / or block diagram of the method, device (system) and computer program product according to the embodiment of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field programmable logic circuit. It can also be understood that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs a specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0184] The above is only a specific implementation of the present invention. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working process of the system, module and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here. It should be understood that the protection scope of the present invention is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be covered within the protection scope of the present invention.

Claims

1. A method for determining network quality, characterized in that: include: Obtaining the signal strength of the mobile terminal within a preset time period; When a first value corresponding to the strength of the signal within the preset time period is greater than or equal to a first threshold, converting the strength of the signal within the preset time period from the time domain to the frequency domain to obtain a target spectrum graph, wherein the first value is a standard deviation or variance of the strength of the signal within the preset time period; Performing image recognition on the target spectrum graph to obtain a recognition result; When the identification result is greater than a preset judgment threshold, determining that the network quality corresponding to the mobile terminal is a first target network quality; When the identification result is less than or equal to a preset judgment threshold, it is determined that the network quality corresponding to the mobile terminal is the second target network quality.

2. The method according to claim 1, characterized in that After acquiring the signal strength of the mobile terminal within a preset time period, the method further includes: When a first value corresponding to the strength of the signal within the preset time period is less than the first threshold, comparing a second value corresponding to the strength of the signal within the preset time period with a second threshold, the second value being an average value of the strength of the signal within the preset time period; If the second value corresponding to the signal strength within the preset time period is less than the second threshold, it is determined that the network quality corresponding to the mobile terminal is the third target network quality.

3. The method according to claim 1, characterized in that When the first value corresponding to the strength of the signal in the preset time period is greater than or equal to the first threshold, converting the strength of the signal in the preset time period from the time domain to the frequency domain to obtain a target frequency spectrum diagram, including: The signal strengths within the preset time period are spliced ​​in chronological order to obtain a target signal strength waveform; Slicing the target signal strength waveform to obtain a plurality of target image frame data; Performing fast Fourier transform processing on the plurality of target image frame data respectively to obtain a plurality of frame spectrum data; The target spectrum graph is obtained by combining the multiple frame spectrum data.

4. The method according to claim 3, characterized in that The step of splicing the signal strengths within the preset time period in chronological order to obtain a target signal strength waveform diagram includes: The signal strengths within the preset time period are spliced ​​in chronological order to obtain an initial target signal strength waveform; Acquire a signal strength point in the initial target signal strength waveform whose difference with any signal strength point is greater than a preset screening threshold as a discrete point; The discrete points in the initial target signal strength waveform are deleted to obtain a target signal strength waveform.

5. The method according to claim 3, characterized in that: The step of slicing the target signal strength waveform to obtain a plurality of target image frame data includes: Slicing the target signal strength waveform diagram according to a preset repetition degree to obtain a plurality of initial image frame data, wherein the preset repetition degree is used to intercept a maximum periodic waveform; The multiple initial image frame data are normalized to obtain multiple target image frame data.

6. The method according to claim 1, characterized in that The first target network quality includes a fourth target network quality and a fifth target network quality. When the identification result is greater than a preset judgment threshold, after determining that the network quality corresponding to the mobile terminal is the first target network quality, the method further includes: Comparing the second value corresponding to the strength of the signal within the preset time period with the second threshold value to obtain a comparison result; When the comparison result indicates that the second value corresponding to the signal strength within the preset time period is greater than or equal to the second threshold, determining that the network quality corresponding to the mobile terminal is the fourth target network quality; When the comparison result indicates that the second value corresponding to the signal strength within the preset time period is less than the second threshold, it is determined that the network quality corresponding to the mobile terminal is the fifth target network quality.

7. The method according to claim 1, characterized in that After performing image recognition on the target spectrum graph to obtain a recognition result, the method further includes: Dividing the number of mobile terminals with the same network quality type by the total number of terminals to obtain target confidence information, where the total number of terminals includes the mobile terminal; The user network quality type is determined based on the target confidence information.

8. A device for determining network quality, characterized in that: The device comprises An acquisition module, the acquisition module is used to acquire the signal strength of the mobile terminal within a preset time period; A conversion module, wherein the conversion module is used to convert the intensity of the signal within the preset time period from the time domain to the frequency domain to obtain a target spectrum diagram when a first value corresponding to the intensity of the signal within the preset time period is greater than or equal to a first threshold, and the first value is a standard deviation or variance of the intensity of the signal within the preset time period; A recognition module, wherein the recognition module is used to perform image recognition on the target spectrum graph to obtain a recognition result; A determination module, the determination module being used to determine, when the identification result is greater than a preset judgment threshold, that the network quality corresponding to the mobile terminal is a first target network quality; The determination module is further configured to determine, when the identification result is less than or equal to a preset judgment threshold, that the network quality corresponding to the mobile terminal is the second target network quality.

9. A device for determining network quality, characterized in that The device comprises: a processor and a memory storing computer program instructions; the processor reads and executes the computer program instructions to implement the method for determining network quality according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the method for determining network quality according to any one of claims 1 to 7 is implemented.

11. A computer program product, characterized in that The invention comprises a computer program, which, when executed by a processor, implements the method for determining network quality according to any one of claims 1 to 7.

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